To test the effectiveness of a job training program on the subsequent wages of workers, suppose

we estimate the following model using individual level data:

log(wagei) =b0 + b1 traini+ b2 educi + b3 experi + b4 part-timei + ui (3)

where train=1 if a worker participated in the program and =0 otherwise, educ=the years of

education a worker has, exper=the number of years of work experience the worker has, and parttime=

1 if the worker held a part-time job(<30hrs>

contains unobserved worker ability (or motivation or enthusiasm).

a) If less able workers have a greater chance of being selected for (and participate in) the program,

and you use an OLS analysis, what can you say about the likely bias in the OLS estimator of b1?

Explain/show how you arrived at this expectation of the bias.

b) Suppose that all of the workers in our sample are part-time workers. If we estimated equation (3),

would multicollinearity be problem? Explain why or why not.